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» A Preference Model for Structured Supervised Learning Tasks
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ICML
2010
IEEE
14 years 10 months ago
Climbing the Tower of Babel: Unsupervised Multilingual Learning
For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally o...
Benjamin Snyder, Regina Barzilay
ICML
2009
IEEE
15 years 10 months ago
A majorization-minimization algorithm for (multiple) hyperparameter learning
We present a general Bayesian framework for hyperparameter tuning in L2-regularized supervised learning models. Paradoxically, our algorithm works by first analytically integratin...
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
ACL
2009
14 years 7 months ago
Better Word Alignments with Supervised ITG Models
This work investigates supervised word alignment methods that exploit inversion transduction grammar (ITG) constraints. We consider maximum margin and conditional likelihood objec...
Aria Haghighi, John Blitzer, John DeNero, Dan Klei...
ICCV
2011
IEEE
13 years 9 months ago
Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Steven Branson, Pietro Perona, Serge Belongie
ECML
2004
Springer
15 years 3 months ago
Model Approximation for HEXQ Hierarchical Reinforcement Learning
HEXQ is a reinforcement learning algorithm that discovers hierarchical structure automatically. The generated task hierarchy repthe problem at different levels of abstraction. In ...
Bernhard Hengst